The invention relates to methods for acquisition of shapes of images with representations of HEp-2 cell sections as objects and for learning abstract shape models from representations of HEp-2 cell sections for a case database for a case-based recognition of HEp-2 cells in the digital images; methods for acquisition of shapes of images with representations of HEp-2 cell sections as cases and for a case-based recognition of HEp-2 cells as objects in digital images; computer program products with a program code for performing these methods; computer program products on machine-readable carriers for performing these methods; and digital storage media that can interact with a programmable computer system in such a way such that these methods are carried out.
Arrangements for automatic examination of cells, cell complexes and other biological samples are disclosed, inter alia, in DE 196 16 997 A1 (method for automated microscope-supported examination of tissue samples or body fluid samples), DE 42 11 904 A1 (method and devices for providing a species list for a liquid sample), and DE 196 39 884 A1 (pattern recognition system).
According to DE 19616 997 A1, tissue samples or body fluid samples are examined with regard to cell types by application of a neuronal network.
Minute living beings such as worms, insects or snails are acquired and identified in DE 42 11 904 A1. The identification is done by comparison with objects contained in a reference object memory. At the same time, the identified objects are counted and inserted into a species list.
In DE 196 39 884 A1 solid components in a sample flow are acquired with regard to their size in particular in accordance with their projection length in the image along the X axis and the Y axis, their circumference, and their average color density. The diagnostics by means of immunofluorescence according to the principle of fluorescence-optical assay of autoantibody binding is performed on frozen sections of HEp-2 cells. This method provides the most reliable results and provides a safe basis for therapeutic decisions.
A disadvantage is the currently missing automation so that a high personnel expenditure is required in connection with a health-hazardous, time-consuming evaluation that requires much experience.
An automated method is disclosed in DE 198 01 400 C2 (method and arrangement for automated recognition, property description, and interpretation of HEp-2 cell patterns). In this connection, only the shapes in the images are recognized. Automated inference in regard to other cases is not provided.